We present a method for unsupervised discovery of abnormal occurrences of activities in multi-dimensional time series data. Unsupervised activity discovery approaches differ from ...
Orbital branching is a method for branching on variables in integer programming that reduces the likelihood of evaluating redundant, isomorphic nodes in the branch-and-bound proce...
James Ostrowski, Jeff Linderoth, Fabrizio Rossi, S...
Accessing structured data in the form of ontologies requires training and learning formal query languages (e.g., SeRQL or SPARQL) which poses significant difficulties for non-expe...
We propose to combine two approaches for modeling data admitting sparse representations: on the one hand, dictionary learning has proven effective for various signal processing ta...
: At Leiden Embedded Research Center (LERC), we are building a tool chain called Compaan/Laura that allows us to map rapidly and efficiently signal processing applications written ...
Steven Derrien, Alexandru Turjan, Claudiu Zissules...